{"id":16690,"date":"2026-07-17T02:22:43","date_gmt":"2026-07-17T02:22:43","guid":{"rendered":"https:\/\/ssktravels.org\/?p=16690"},"modified":"2026-07-17T02:22:43","modified_gmt":"2026-07-17T02:22:43","slug":"dots-mocr-on-copilot-pc-direct-exe-setup","status":"publish","type":"post","link":"https:\/\/ssktravels.org\/index.php\/2026\/07\/17\/dots-mocr-on-copilot-pc-direct-exe-setup\/","title":{"rendered":"dots.mocr on Copilot+ PC Direct EXE Setup"},"content":{"rendered":"<p><img decoding=\"async\" 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alt=\"dots.mocr on Copilot+ PC Direct EXE Setup\" style=\"width:100%;height:auto;border-radius:8px\"><\/p>\n<p>Deploying this model locally is <i>quickest<\/i> when done via a simple <b>curl command<\/b>.<\/p>\n<p>Execute the <b>commands and steps<\/b> outlined below.<\/p>\n<p> <\/p>\n<p><i>An automated background process downloads all required large-scale files.<\/i><\/p>\n<p> <\/p>\n<p>Without any user input, the software <b>calibrates parameters for optimal hardware usage<\/b>.<\/p>\n<table style=\"width:800px;max-width:800px;margin:10px auto 60px;border-collapse:collapse;border-radius:14px;overflow:hidden;font-family:-apple-system,BlinkMacSystemFont,'Segoe UI',Roboto,Helvetica,Arial,sans-serif;background:#ffffff;border:1px solid #edf2f7\">\n<tr>\n<td style=\"padding:42px 52px;text-align:center;font-size:22px;color:#4a5568;line-height:2.2;letter-spacing:-0.01em\">\n<div style=\"text-align: left;font-size:11px\">\n<div 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By integrating vision and language modules, it extracts text from diverse sources such as scanned images, handwritten notes, and natural-scene photos with unprecedented accuracy. With a parameter count of 1.5B, this cutting-edge model efficiently runs on consumer GPUs while delivering real-time inference speeds. This innovative architecture incorporates an attention-based layout analyzer that preserves structural relationships, enabling downstream tasks like data entry and content summarization. The modular design of dots.mocr empowers developers to fine-tune specific components, making it a versatile choice for enterprise workflow automation.<\/p>\n<ul style=\"list-style-type: upper-alpha\">\n<li> Supports multiple input formats, including PDF, JPG, PNG, and handwritten documents.<\/li>\n<li> Achieves an impressive 90% word-error-rate reduction on benchmark datasets compared to legacy solutions.<\/li>\n<li> Employs an attention-based layout analyzer to preserve structural relationships in the extracted text.<\/li>\n<\/ul>\n<table style=\"border-collapse: collapse\">\n<tr>\n<th style=\"border:1px solid #ccc\">Specification<\/th>\n<th style=\"border:1px solid #ccc\">Value<\/th>\n<\/tr>\n<tr>\n<td style=\"border:1px solid #ccc\">Parameters<\/td>\n<td style=\"border:1px solid #ccc\">1.5 B<\/td>\n<\/tr>\n<tr>\n<td style=\"border:1px solid #ccc\">Input Types<\/td>\n<td style=\"border:1px solid #ccc\">PDF, JPG, PNG, Handwritten<\/td>\n<\/tr>\n<tr>\n<td style=\"border:1px solid #ccc\">Supported Languages<\/td>\n<td style=\"border:1px solid #ccc\">100<\/td>\n<\/tr>\n<tr>\n<td style=\"border:1px solid #ccc\">Inference Speed<\/td>\n<td style=\"border:1px solid #ccc\">&gt;30 fps on RTX 3080<\/td>\n<\/tr>\n<\/table>\n<p><q>Key Benefits of dots.mocr:<\/q>* <\/p>\n<ul style=\"list-style-type: upper-alpha\">\n<li> High-speed document processing with unprecedented accuracy.<\/li>\n<li> Real-time inference speeds for efficient workflow automation.<\/li>\n<li> Modular design allows developers to fine-tune specific components.<\/li>\n<\/ul>\n<p><q>Real-World Applications:<\/q>* <\/p>\n<p>Dots.mocr is poised to revolutionize enterprise workflow automation by providing a flexible and scalable solution for document processing.<\/p>\n<h4>Unlocking Efficient Document Processing with dots.mocr<\/h4>\n<p>The dots.mocr model revolutionizes document processing by harnessing the power of multimodal OCR. By integrating vision and language modules, it extracts text from diverse sources such as scanned images, handwritten notes, and natural-scene photos with unprecedented accuracy. With a parameter count of 1.5B, this cutting-edge model efficiently runs on consumer GPUs while delivering real-time inference speeds. This innovative architecture incorporates an attention-based layout analyzer that preserves structural relationships, enabling downstream tasks like data entry and content summarization. The modular design of dots.mocr empowers developers to fine-tune specific components, making it a versatile choice for enterprise workflow automation.<\/p>\n<ul style=\"list-style-type: upper-alpha\">\n<li> Supports multiple input formats, including PDF, JPG, PNG, and handwritten documents.<\/li>\n<li> Achieves an impressive 90% word-error-rate reduction on benchmark datasets compared to legacy solutions.<\/li>\n<li> Employs an attention-based layout analyzer to preserve structural relationships in the extracted text.<\/li>\n<\/ul>\n<table style=\"border-collapse: collapse\">\n<tr>\n<th style=\"border:1px solid #ccc\">Specification<\/th>\n<th style=\"border:1px solid #ccc\">Value<\/th>\n<\/tr>\n<tr>\n<td style=\"border:1px solid #ccc\">Parameters<\/td>\n<td style=\"border:1px solid #ccc\">1.5 B<\/td>\n<\/tr>\n<tr>\n<td style=\"border:1px solid #ccc\">Input Types<\/td>\n<td style=\"border:1px solid #ccc\">PDF, JPG, PNG, Handwritten<\/td>\n<\/tr>\n<tr>\n<td style=\"border:1px solid #ccc\">Supported Languages<\/td>\n<td style=\"border:1px solid #ccc\">100<\/td>\n<\/tr>\n<tr>\n<td style=\"border:1px solid #ccc\">Inference Speed<\/td>\n<td style=\"border:1px solid #ccc\">&gt;30 fps on RTX 3080<\/td>\n<\/tr>\n<\/table>\n<p><q>Key Benefits of dots.mocr:<\/q>* <\/p>\n<ul style=\"list-style-type: upper-alpha\">\n<li> High-speed document processing with unprecedented accuracy.<\/li>\n<li> Real-time inference speeds for efficient workflow automation.<\/li>\n<li> Modular design allows developers to fine-tune specific components.<\/li>\n<\/ul>\n<p><q>Real-World Applications:<\/q>* <\/p>\n<p>Dots.mocr is poised to revolutionize enterprise workflow automation by providing a flexible and scalable solution for document processing.<\/p>\n<ul>\n<li>Installer deploying offline face recovery modules alongside pre-trained weight array profiles and folders<\/li>\n<li>dots.mocr 100% Private PC No-Internet Version FREE<\/li>\n<li>Installer pre-configuring Automatic1111 WebUI extensions and dependencies<\/li>\n<li>How to Run dots.mocr Windows 11 FREE<\/li>\n<li>Setup tool optimizing CPU core affinity bindings for llama.cpp performance<\/li>\n<li>How to Deploy dots.mocr Offline Setup<\/li>\n<li>Installer deploying local bark audio pipelines with custom speaker prompts<\/li>\n<li>Quick Run dots.mocr Windows 11 Step-by-Step<\/li>\n<li>Script downloading modern ControlNet depth models for Forge WebUI<\/li>\n<li>How to Setup dots.mocr FREE<\/li>\n<li>Script automating parallel down-streaming of sharded Hugging Face model chunks<\/li>\n<li>dots.mocr<\/li>\n<\/ul>\n","protected":false},"excerpt":{"rendered":"<p>Deploying this model locally is quickest when done via a simple curl command. Execute the commands and steps outlined below.<\/p>\n","protected":false},"author":3,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[135],"tags":[],"class_list":["post-16690","post","type-post","status-publish","format-standard","hentry","category-custom"],"_links":{"self":[{"href":"https:\/\/ssktravels.org\/index.php\/wp-json\/wp\/v2\/posts\/16690"}],"collection":[{"href":"https:\/\/ssktravels.org\/index.php\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/ssktravels.org\/index.php\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/ssktravels.org\/index.php\/wp-json\/wp\/v2\/users\/3"}],"replies":[{"embeddable":true,"href":"https:\/\/ssktravels.org\/index.php\/wp-json\/wp\/v2\/comments?post=16690"}],"version-history":[{"count":1,"href":"https:\/\/ssktravels.org\/index.php\/wp-json\/wp\/v2\/posts\/16690\/revisions"}],"predecessor-version":[{"id":16691,"href":"https:\/\/ssktravels.org\/index.php\/wp-json\/wp\/v2\/posts\/16690\/revisions\/16691"}],"wp:attachment":[{"href":"https:\/\/ssktravels.org\/index.php\/wp-json\/wp\/v2\/media?parent=16690"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/ssktravels.org\/index.php\/wp-json\/wp\/v2\/categories?post=16690"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/ssktravels.org\/index.php\/wp-json\/wp\/v2\/tags?post=16690"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}